Signal-to-noise ratio (SNR) determination in the time domain

ABSTRACT

A technique for modifying communication operational parameters using fast, low complexity, accurately calculated SNR values. Techniques may improve upon prior art by calculating SNR values in a more time efficient and accurate manner in time domain. An agent may be implemented to calculate SNR values and either store or use the SNR values to modify operational parameters in communicative system.

RELATED APPLICATIONS

The present U.S. patent application is related to the following U.S.patent application filed concurrently application Ser. No. 11/______(Docket No. P24582), filed Jun. 30, 2006, entitled “SIGNAL-TO-NOISERATIO (SNR) DETERMINATION IN THE FREQUENCY DOMAIN.”

TECHNICAL FIELD

Embodiments of the invention relate to wireless communication andbroadband access. More particularly, embodiments of the invention relateto determination of data connection parameters using Signal to NoiseRatio (SNR) values of communication signals.

BACKGROUND

Signal to Noise Ratio (SNR) is one of the key statistics in determiningoperational parameters between devices communicating with one another.Accurate SNR measurements are crucial for determining ultimate datatransmission parameters, especially in IEEE 802.16 standard basedwireless product development. IEEE 802.16 corresponds to IEEE Std.802.16-2004 “IEEE Standard for Local and Metropolitan Area Networks Part16: Air Interface for Fixed Broadband Wireless Access Systems” and IEEEStd. 802.16e-2005 “IEEE Standard for Local and Metropolitan AreaNetworks Part 16: Air Interface for Fixed and Mobile Broadband WirelessAccess Systems.” Fast SNR measurements and calculations are key toimproving the speed of the data transmission.

It has been challenging to engineer an accurate and low complexity SNRalgorithm. SNR calculations have typically been conducted in the timedomain using time expensive square root functions. To determine SNRvalues, typically a signal is received in a device. Such signal may berepresented as: r_(k), where k=0, 1, . . . , 255. The SNR valuetypically is calculated as:

${SNR} = {\frac{X}{{E - {X}}}\mspace{14mu} {in}\mspace{14mu} {linear}}$

where,

${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}}$

and |X| is the absolute value of complex data X and calculated as|X|=√{square root over ((real(X))²+(imag(X))²)}{square root over((real(X))²+(imag(X))²)}. This square root operation is a very timecostly operation.

Thus, in order to improve data transmission in wireless devices thereexists a need for more efficient, accurate, and noise insensitivetechniques to determine SNR value for signals received in wirelesscommunication devices.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention are illustrated by way of example, and notby way of limitation, in the figures of the accompanying drawings inwhich like reference numerals refer to similar elements.

FIG. 1 is a conceptual diagram of one embodiment of a communicativenetwork.

FIG. 2 a is a conceptual diagram of one embodiment of a preamble symbolstructure and frequency domain subcarriers.

FIG. 2 b is a conceptual diagram of one embodiment of a preamble symbolstructure.

FIG. 3 is a block diagram of one embodiment of a device including an SNRdetermination agent to determine a signal-to-noise ratio that may beutilized to select or modify operational parameters.

FIG. 4 is a conceptual diagram of one embodiment of a SNR determinationagent that may determine SNR values in the time domain.

FIG. 5 is a flow diagram of one embodiment of a technique forcalculating SNR values in the time domain.

FIG. 6 is a conceptual diagram of one embodiment of a SNR determinationagent that may determine SNR values in the frequency domain.

FIG. 7 is a flow diagram of one embodiment of a technique forcalculating SNR values in the frequency domain.

FIG. 8 is a conceptual diagram of one embodiment of a SNR determinationagent that may determine SNR values in the frequency domain.

FIG. 9 is a flow diagram of one embodiment of a technique forcalculating SNR values in the frequency domain.

FIG. 10 is a conceptual diagram of one embodiment of an agent that maybe used for calculating ACI SNR values.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth.However, embodiments of the invention may be practiced without thesespecific details. In other instances well-known circuits, structures andtechniques have not been shown in detail in order not to obscure theunderstanding of this description.

Signal to Noise Ratio (SNR) values are key in determining communicativeconnections. Efficient calculation of SNR values may help to improve theset up time of data connections. Described herein in are varioustechniques for relatively low complexity, color noise insensitive SNRdeterminations.

FIG. 1 is a conceptual diagram of one embodiment of a wireless network.The wireless network may support any number of different protocols knownin the art. Base station 110 may provide an access point for wirelesscommunication for one or more mobile devices, such as, for example,wireless cellular device 130 or palm held device 120. In otherembodiments, a transmitting station or an access point, may replace basestation 110. Any number of wireless devices may be supported. A wirelessmobile device may be, for example, a cellular telephone, a laptopcomputer, a personal digital assistant, a smart phone, or any otherwireless-enabled device. In other embodiments, broadband devices may besupported in a wired network, such as, for example, modem 140.

SNR values may be used in wireless cellular device 130 or base station110 to modify operational parameters for data connections. In alternateembodiments, SNR values may be calculated in wireless devices, broadbandwired devices, access points, or any combination thereof. In oneembodiment, the SNR values may be used to set up, modify, determine, oradjust operational parameters or settings. Operational parameters mayaffect communication signals connection, transmission, reception or anycombination thereof.

FIG. 2 a is a conceptual diagram of one embodiment of a received signalstructure for which SNR values may be calculated. In one embodiment,signal symbol structure 210 a may include copy samples 215 a at thebeginning of the symbol structure 210 a. The copy samples 215 a may beskipped during SNR calculation. In one embodiment, the signal may have atime-domain 128 sample periodic structure. The first portion P₁ 216 amay be symmetric with the second signal symbol portion P₂ 217 a. Thesamples may be fixed or varying in length. In alternate embodiments,other signal structures may be received. Frequency domain subcarriers220 a may correspond to signal symbol structure 210 a.

FIG. 2 b is a conceptual diagram of one embodiment of a received signalstructure for which SNR values may be calculated. In one embodiment,signal symbol structure 210 b may contain a first portion P₁ 216 b and asecond signal symbol portion P₂ 217 b. Signal symbol structure 210 b mayuse the orthogonal frequency-division multiplexing property of cyclicprefix. First portion P₁ 216 b may be symmetric to second signal symbolportion P₂ 217 b. In alternate embodiments, other signal structures withsymmetric properties may be received. In other embodiments, frequencydomain subcarriers 220 a may correspond to signal symbol structure 210b.

FIG. 3 is a block diagram of one embodiment of a device including an SNRcalculation agent 315. In one embodiment, SNR calculation agent 315 maycalculate SNR values and determine operational parameters based on thecalculated value. SNR calculation agent 315 may be implemented inhardware, software, firmware, or any combination thereof.

Device 300 may be implemented in a receiving, transmitting, wireless,broadband wired, access point or any combination of these type ofdevice. Alternative devices may include more, fewer and/or differentcomponents. Device 300 may include bus 305 or other communication deviceto communicate information, and processor 360 coupled to bus 305 thatmay process information. While device 300 is illustrated with a singleprocessor, device 300 may include multiple processors and/orco-processors.

Device 300 further may include random access memory (RAM) or otherdynamic storage device 310, coupled to bus 305 and may store informationand instructions that may be executed by processor 360. Memory 310 maybe used to store temporary variables or other intermediate informationduring execution of instructions by processor 360. Memory 310 mayinclude any type of memory known in the art, for example, dynamic randomaccess memory (DRAM), static random access memory (SRAM), flash memory,etc. In one embodiment, memory 310 may include any type ofcomputer-readable storage medium that provides content (e.g., computerexecutable instructions) in a form readable by an electronic device(e.g., a computer, a personal digital assistant, a cellular telephone).For example, a machine-accessible medium includes read only memory(ROM); random access memory (RAM); magnetic disk storage media; opticalstorage media; flash memory devices; etc.

Memory 310 may further include SNR determination agent 315. The processof agent 315 may be implemented as instructions stored in memory 310that are executed by processor 360. Alternatively, agent 315 may becoupled to the bus, (not shown), as an independent circuitry that mayinteract with processor 360. Each unit of agent 315 may be implementedas hardware, software, firmware, or a combination of these.

Device 300 may also include read only memory (ROM) 340 and/or otherstatic storage device 330 coupled to bus 305 to store information andinstructions. Data storage device 330 may be a magnetic disk or opticaldisk and the corresponding drives may be coupled to device 300.

Device 300 may further include network interface(s) 320 to provideaccess to a network. Network interface(s) may include, for example, awireless network interface having one or more omnidirectional antennae385. Network interface(s) 320 may also include, for example, a wirednetwork interface to communicate with remote devices via network cable387, which may be, for example, an Ethernet cable, a coaxial cable, afiber optic cable, a serial cable, or a parallel cable. Device 300 mayinclude additional and/or different components.

FIG. 4 is a conceptual diagram of one embodiment of an SNR determinationagent. Agent 315 in FIG. 4 may correspond to agent 315 in FIG. 3. Inthis embodiment, SNR calculation agent 315 may calculate SNR values inthe time domain, while providing an improvement over prior SNRcalculating method in the time domain by decreasing complexity andincreasing time efficiency

In one embodiment, agent 315 may receive a signal structure at signalreception unit 410. The signal may be received from network interface320 in FIG. 3. In one embodiment, the received signal structure issimilar to that of symbol structure 210 a in FIG. 2 a. Alternateembodiments may have alternate signal structures, such as, for example,symbol structure 210 b in FIG. 2 b.

SNR approximation unit 420 may calculate an approximate SNR value usinga first SNR equation based on the signal received at signal receptionunit 410. Comparison unit 430 may then compare the calculatedapproximate SNR value with a threshold value. The threshold value maybe, for example, 3 dB; however, other threshold values (e.g., 6 dB, 10dB) may also be used. In one embodiment, if the approximate SNR is lowerthan the threshold as determined by comparison unit 430, recalculationand modification unit 440 may determine operational parameters based onthe approximate SNR value calculated by unit 420. If the approximate SNRvalue is higher than the preset threshold, unit 440 may recalculate theSNR value using a different calculation technique (e.g., a second SNRequation) and may cause operational parameters to be modified based, atleast in part on, the recalculated SNR value.

In alternate embodiments, agent 315 may also be composed of other unitscarrying on the same functionality. Example equations that may be usedto determine the SNR value are described below with respect to FIG. 5.

FIG. 5 is a flow diagram of one embodiment of a technique forcalculating SNR values in the time domain. The technique flow of FIG. 5may correspond to the functionality of agent 315 in FIG. 4. Thetechniques described herein may be applied to any SNR calculationenvironment. In one embodiment, the technique may be implemented in thetime domain while reducing the complexity of prior art techniques thatrely on using an expensive square root function.

A signal may be received, 510. The signal may be received in any mannerknown in the art. The signal may be received at signal reception 410. Inone embodiment, the signal may be of preamble symbol structure 210 a inFIG. 2 a. Preamble 210 a may be a time-domain signal composed of apreset number of copy samples followed by two symmetrical 128 samplelong structures. Preamble 210 a may be 128 samples periodic. In oneembodiment, the preamble symbol structure may be boosted by 6 dB toimprove reception. Alternate symbol structures may be used in otherembodiments, such as, for example, symbol structure 210 b in FIG. 2 b.

An approximate SNR value may be calculated, 520, and may be calculatedby calculation unit 420. In one embodiment, the approximate SNR may becalculated as:

SNR=(log₂ |X|−log₂ |E−|X∥)(log₁₀ 2)

where,

${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k} \cdot r_{k + 128}^{*}}}}},$

r*_(k+128), value of E is determined as

${E = {{\sum\limits_{k = 0}^{255}\; {r_{k} \cdot r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$

where r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵ with {s_(k)}_(k=0) ¹²⁷being one half of the (2×128)-preamble and {n_(k)}_(k=0) ²⁵⁵ beingAdditive White Gaussian Noise (AWGN). In one embodiment, log₁₀ 2 may beapproximated by

$\frac{1233}{2^{12}}.$

In one embodiment, the approximate value of |X| may be available.

The approximate SNR value may be compared with a threshold value, 530,and may be performed by comparison unit 430. In one embodiment, thethreshold values may be 6 dB or 10 dB. In alternate embodiments otherthreshold values may be used.

If the SNR value is lower than the preset threshold value, operation 530may direct the flow to operation 540. Operation 540 may then modifyoperational transmission parameters based, at least in part, on theapproximate SNR value. Unit 440 may modify operational transmissionparameters based, at least in part, on the approximate SNR value. Inalternate embodiments, operational parameters may be modified, set up,or determined based, at least in part, on the SNR value. Operationalparameters may include data settings of reception, connection,transmission, or any combination thereof. The SNR value may also bestored to be used in future calculations and determinations.

However, if operation 530 determines that the approximate SNR value tobe higher than the threshold value, operation 530 may then direct thetechnique flow to operation 550 to recalculate the SNR value. Unit 440may perform the SNR recalculation. Operation 550 may recalculate SNR as:

SNR=(log₂(2|X| ²)−log₂ |E ² −|X| ²|)(log₁₀ 2),

where

${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k} \cdot r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k} \cdot r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$

where r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵ with {s_(k)}_(k=0) ¹²⁷being one half of the (2×128)-preamble and {n_(k)}=_(k=0) ²⁵⁵ being AWGNnoises. In one embodiment log₁₀ 2 may be approximated as

$\frac{1233}{2^{12}}.$

In one embodiment |X|² may be determined by |X|²=(X_(re) ²+X_(im) ²).

Operation 550 may then modify operational parameters based, at least inpart, on the calculated SNR value. Unit 440 may perform themodification. In alternate embodiments, operational parameters may bemodified, set up, or determined based, at least in part on the SNRvalue. Operational parameters may include data settings of reception,connection, transmission, or any combination thereof. The SNR value mayalso be stored to be used in future calculations and determinations.

FIG. 6 is a conceptual diagram of one embodiment of an SNR determinationagent. Agent 315 in FIG. 6 may correspond to agent 315 in FIG. 3. In oneembodiment, SNR calculation agent 315 may calculate SNR values in thefrequency domain, where lower complexity and thus lower time costs maybe achieved. Frequency domain calculations are more insensitive tovarious color-noises, such as adjacent-channel interference (ACI) andcontinuous waveform (CW) interference noises. Thus, at least one SNRcalculation technique has the added advantage of being more insensitiveto “color-noise” interference than prior art techniques. The functionalunits of FIG. 6 may be implemented as hardware, software, firmware, orany combination thereof.

In one embodiment, agent 315 in FIG. 6 may receive a signal structure atsignal reception unit 610. The signal may be received from networkinterface 320 in FIG. 3. In one embodiment, the received signalstructure is similar to that of symbol structure 210 a in FIG. 2 a. Inalternate embodiments, other signal structures may be received, forexample, signal symbol structure 210 b in FIG. 2 b. Time domain tofrequency domain transformation unit 620 may then calculatecorresponding frequency domain subcarriers for the signal received atunit 610. Calculation unit 630 may then calculate noise power with noisepower calculation unit 631 and signal power with signal powercalculation unit 632 based on the frequency domain subcarrierscalculated at unit 620. Example techniques for noise power calculationand signal power calculation are described in greater detail below withrespect to FIG. 7.

SNR ratio calculation and operational parameter modification unit 640may then calculate an SNR value as a ratio of the noise power and signalpower calculated in unit 630. Example techniques for SNR valuecalculation are described in greater detail in FIG. 7. Unit 640 may thenmodify operational parameters based, at least in part, on the calculatedSNR value. In alternate embodiments, agent 315 may also be composed ofother units carrying on the same functionality.

FIG. 7 is a flow diagram of one embodiment of a technique forcalculating SNR values in the frequency domain. The technique flow ofFIG. 7 may correspond to the functionality of agent 315 in FIG. 6. Thetechniques described herein may be applied to any SNR calculationenvironment.

A signal may be received, 710. The signal may be received in any mannerknown in the art. The signal may be received at signal reception unit610. In one embodiment, the signal may be of preamble symbol structure210 a in FIG. 2 a. In alternate embodiments, other signal structure maybe received, for example, signal symbol structure 210 b in FIG. 2 b.Preamble 210 a may be a time-domain signal composed of a preset numberof copy samples followed by two symmetrical 128 sample long structures.Preamble 210 a may be 128 samples periodic. In one embodiment, thepreamble symbol structure may be boosted by 6 dB to improve reception.Alternate symbol structures may be used in other embodiments.

Frequency domain subcarriers corresponding to the received signal may becalculated at operation 720. Time domain to frequency domaintransformation unit 620 may perform the frequency domain subcarrierscalculation. In one embodiment, a Fast Fourier Transformation (FFT) maybe performed to output the frequency domain carriers:

{X _(k) } _(k=0) ²⁵⁵ =FFT({x _(k)}_(k=0) ²⁵⁵),

where {x_(k)}_(k=0) ²⁵⁵ is the time domain signal of the received(2×128)-preamble.

The subcarriers may correspond to subcarriers 220. In alternateembodiments, other type of transformations may be used to calculate thefrequency domain subcarriers, or frequency coefficients, or frequencydomain values. The FFT may be performed over the over symbol blocks P₁216 a and P₂ 217 a.

In alternate embodiments, the FFT may be performed over parts of symbolblocks P₁ 216 a and P₂ 217 a, symbol blocks P₁ 216 b and P₂ 217 b, orparts of symbol blocks P₁ 216 b and P₂ 217 b. The FFT size may depend onthe block size of the data selected. The range of index k may be changedaccordingly.

Operation 730 may use the frequency domain subcarriers calculated atoperation 720 to calculate noise power and signal power of the receivedsignal, and may be performed by unit 631 and unit 632, respectively. Thenoise power may be calculated as:

$P_{n} = {( {{\sum\limits_{k = {1\text{:}2\text{:}99}}{X_{k}}^{2}} + {\sum\limits_{k = {155\text{:}2\text{:}253}}{X_{k}}^{2}}} ).}$

In one embodiment, the noise power may be calculated as a summation ofall the noise tone powers with tone-index ranging from 1 to 99 and 155to 253 with index-step size of two. Other ranges and index-step sizesmay also be used.

Operation 730 may calculate the signal power as:

$P_{s} = {( {{\sum\limits_{k = {2\text{:}2\text{:}100}}{X_{k}}^{2}} + {\sum\limits_{k = {156\text{:}2\text{:}254}}{X_{k}}^{2}}} ) - {P_{n}.}}$

In one embodiment, the noise power may be calculated as a summation ofall the signal tone powers with tone-index ranging from 2 to 100 and 156to 254 with index-step size of two. Other ranges and index-step sizesmay also be used.

Operation 740 may calculate SNR as the ratio between noise power andsignal power calculated in operation 730. Unit 640 may perform operation740. SNR may be calculated as:

${SNR} = {\frac{P_{s}}{P_{n}}.}$

In one embodiment, ratio may be calculated in linear scale. In anotherembodiment SNR may be calculated as:

SNR=(log₂ P _(s)−log₂ P _(n))(log₁₀ 2)−6,

where log₁₀ 2 could be approximated by

$\frac{1233}{2^{12}}$

and the extra 6 dB is subtracted if the preamble pilot-tones are 6 dBboosted.

Operation 750 may then modify operational parameters based, at least inpart on the SNR value calculated at operation 740. Unit 640 may performoperation 750. In alternate embodiments reception, connection,transmission or other operational parameters may be modified, set up, ordetermined based, at least in part on the SNR value. The SNR value mayalso be stored to be used in future calculations and determinations.

FIG. 8 is a conceptual diagram of one embodiment of an SNR determinationagent. Agent 315 in FIG. 8 may correspond to agent 315 in FIG. 3. In oneembodiment, SNR determination agent 315 may calculate SNR values in thefrequency domain and thus provide the added advantage of being moreinsensitive to “color-noise” interference than prior art techniques. Theunits of FIG. 8 may be implemented as hardware, software, firmware, orany combination thereof.

In one embodiment, agent 315 may receive a signal structure at signalreception unit 810. The signal may be received from network interface320 in FIG. 3. In one embodiment, the received signal structure issimilar to that of symbol structure 210 a in FIG. 2 a. In alternateembodiments, other signal structures may be received, for example,signal symbol structure 210 b in FIG. 2 b. Time domain to frequencydomain transformation unit 820 may then calculate correspondingfrequency domain subcarriers for the signal received at unit 810.

Calculation unit 830 may then calculate signal power using signal powercalculation unit 831 and composite signal power with composite signalpower calculation unit 832 based on the frequency domain subcarrierscalculated at unit 820. Example techniques for noise power calculationand signal power calculation are described in greater detail below withrespect to FIG. 9. SNR Ratio Calculation and Operational ParameterModification unit 840 may then calculate an SNR value as a ratio of thesignal power and composite signal power calculated at unit 830. Exampletechniques for SNR value calculation are described in greater detailbelow with respect to FIG. 9. Unit 840 may then modify operationalparameters based, at least in part, on the calculated SNR value. Inalternate embodiments, agent 315 may also be composed of other unitscarrying on the similar functionality.

FIG. 9 is a flow diagram of one embodiment of a technique forcalculating SNR values in the frequency domain. The technique flow ofFIG. 9 may correspond to the functionality of agent 315 in FIG. 8. Thetechniques described herein may be applied to any SNR calculationenvironment.

A signal may be received, 910. The signal may be received in any mannerknown in the art. The signal may be received at signal reception unit810. In one embodiment, the signal may be of preamble symbol structure210 a in FIG. 2 a. In alternate embodiments, other signal structures maybe received, for example, signal symbol structure 210 b in FIG. 2 b.Preamble 210 a may be a time-domain signal composed of a preset numberof copy samples followed by two symmetrical 128 sample long structures.Preamble 210 a may be 128 samples periodic. In one embodiment, thepreamble symbol structure may be boosted by 6 dB to improve reception.Alternate symbol structures may be used in other embodiments.

Frequency domain subcarriers corresponding to the received signal may becalculated at operation 920. Time domain to frequency domaintransformation unit 820 may perform operation 920. In one embodiment,two Fast Fourier Transformation (FFT) may be performed on the first andsecond halves of the symbol structure of the received signal in order tooutput the frequency domain carriers:

X _(1,k) =FFT({x _(n)}_(n=0) ¹²⁷) X _(2,k) =FFT({x _(n)}_(n=128) ²⁵⁶),

where {x_(k)}_(k=0) ²⁵⁵ is the time domain signal of the received(2×128)-preamble.

The subcarriers may correspond to subcarriers 220. In alternateembodiments, other type of transformations may be used to calculate thefrequency domain subcarriers, or frequency coefficients, or frequencydomain values. The FFT may be performed over the over symbol blocks P₁216 a and P₂ 217 a.

In alternate embodiments, the FFT may be performed over parts of symbolblocks P₁ 216 a and P₂ 217 a, symbol blocks P₁ 216 b and P₂ 217 b, orparts of symbol blocks P₁ 216 b and P₂ 217 b. The FFT size may depend onthe block size of the data selected. The range of index k may be changedaccordingly.

Operation 930 may calculate signal power and composite signal power ofthe received signal based on the frequency domain subcarriers calculatedat operation 920. Unit 830 may perform calculations of operation 930.The signal power may be calculated as:

$P_{s} = {{{{\sum\limits_{k = {1\text{:}1\text{:}49}}{X_{1,k}X_{2,k}^{*}}} + {\sum\limits_{k = {78\text{:}1\text{:}127}}{X_{1,k}X_{2,k}^{*}}}}}.}$

Operation 930 may calculate the composite signal power as:

$P_{c} = {{\sum\limits_{k = {1\text{:}1\text{:}49}}{X_{1,k}}^{2}} + {\sum\limits_{k = {78\text{:}1\text{:}127}}{X_{1,k}}^{2}} + {\sum\limits_{k = {1\text{:}1\text{:}49}}{X_{2,k}}^{2}} + {\sum\limits_{k = {78\text{:}1\text{:}127}}{{X_{2,k}}^{2}.}}}$

Operation 940 may calculate SNR as a ratio between signal power andcomposite signal power calculated in operation 930. Operation 940 may beperformed in unit 840. SNR may be calculated as:

${SNR} = {\frac{2P_{s}}{P_{c} - {2P_{s}}}.}$

In one embodiment, ratio may be calculated in linear scale. In anotherembodiment SNR may be calculated as:

SNR=(log₂(2P _(s))−log₂(P _(c)−2P _(s)))(log₁₀ 2)−6,

where log₁₀ 2 could be approximated by

$\frac{1233}{2^{12}}$

and the extra 6 dB is subtracted because the preamble pilot-tones are 6dB boosted.

Operation 950 may then modify operational parameters based on thecalculated SNR value. Unit 840 may perform operation 950. In alternateembodiments, reception, connection, transmission or other operationalparameters may be modified, set up, or determined based, at least inpart on the SNR value. The SNR value may also be stored to be used infuture calculations and determinations.

FIG. 10 is a conceptual diagram of an agent 315 that may be used fordetermining adjacent channel interference (ACI) SNR values. SignalReception Unit 1000 may receive a signal. The signal may then be passedto Time Domain SNR Calculation Device 1010 and Frequency Domain SNRCalculation Device 1020, which may calculate SNR values in the time andfrequency domain respectively. The techniques used by Time Domain SNRCalculation Device 1010 to calculate the time domain SNR value maycorrespond to technique flow 500 in FIG. 5.

The techniques used by Frequency Domain SNR Calculation Device 1020 tocalculate the frequency domain SNR value may correspond to techniqueflow 700 in FIG. 7, or technique flow 900 in FIG. 9. Operation 1030 maythen calculate the SNR_(ACI), signal to noise ratio for adjacent channelinterference, as the absolute value of the difference between thefrequency domain SNR value and the time domain SNR value. The SNR_(ACI)value may be used to determine ACI severity measurement 1040. TheSNR_(ACI) value may help optimize the system performance by, forexample, switching to frequency bands based on the SNR_(ACI) value.

Reference in the specification to “one embodiment” or “an embodiment”means that a particular feature, structure or characteristic describedin connection with the embodiment is included in at least one embodimentof the invention. The appearances of the phrase “in one embodiment” invarious places in the specification are not necessarily all referring tothe same embodiment.

While the invention has been described in terms of several embodiments,those skilled in the art will recognize that the invention is notlimited to the embodiments described, but can be practiced withmodification and alteration within the spirit and scope of the appendedclaims. The description is thus to be regarded as illustrative insteadof limiting.

1. A method of calculating Signal to Noise Ratio (SNR) comprising:calculating a first SNR value for a received signal using a first SNRequation; comparing the first SNR value against a threshold value;calculating a second SNR value using a second SNR equation based on theresult of the comparison; and utilizing the second SNR value toselectively modify operational parameters.
 2. The method of claim 1wherein the first SNR equation comprises(log₂ |X|−log₂ |E−|X∥)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ¹²⁷, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being Additive WhiteGaussian Noise (AWGN).
 3. The method of claim 1 wherein calculating asecond SNR value using a second SNR equation based on the result of thecomparison comprises setting the second SNR value equal to the first SNRvalue if the first SNR value is lower than the threshold.
 4. The methodof claim 1 wherein the second SNR equation comprises:(log₂(2|X| ²)−log₂ |E ² −|X| ²|)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵ with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being AWGN noises, tocalculate the second SNR value if the first SNR value is greater thanthe threshold.
 5. The method of claim 1 wherein selective modificationof operational parameters comprises one or more of adjusting, setting,and determining operational parameters and further wherein theoperational parameters comprise one or more of data connectionparameters, data connection settings, data transmission parameters, anddata transmission settings.
 6. The method of claim 1 further comprisinggenerating a quality value based, at least in part, on a differencebetween the second SNR value and a frequency domain calculated SNRvalue.
 7. The method of claim 6 further comprising selectively switchingfrequency bands based on the quality value generated.
 8. An apparatuscomprising: a communication interface to communicate utilizing wirelesscommunication protocols; and an agent coupled with the communicationinterface to calculate a first SNR value for a received signal using afirst SNR equation, to compare the first SNR value against a thresholdvalue, to calculate a second SNR value using a second SNR equation basedon the result of the comparison and to utilize the second SNR value toselectively modify operational parameters.
 9. The apparatus of claim 8wherein the first SNR equation comprises(log₂ |X|−log₂ |E−|X∥)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being Additive WhiteGaussian Noise (AWGN).
 10. The apparatus of claim 8 wherein calculatinga second SNR value using a second SNR equation based on the result ofthe comparison comprises setting the second SNR value equal to the firstSNR value if the first SNR value is lower than the threshold.
 11. Theapparatus of claim 8 wherein the second SNR equation comprises:(log₂(2|X| ²)−log₂|E² −|X| ²|)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being AWGN noises, tocalculate the second SNR value if the first SNR value is greater thanthe threshold.
 12. The apparatus of claim 8 wherein selectivemodification of operational parameters comprises one or more ofadjusting, setting, and determining operational parameters and furtherwherein the operational parameters comprise one or more of dataconnection parameters, data connection settings, data transmissionparameters, and data transmission settings.
 13. The apparatus of claim8, wherein the agent is further configured to generate a quality valuebased, at least in part, on a difference between the second SNR valueand a frequency domain calculated SNR value.
 14. The apparatus of claim13, wherein the agent is further configured to selectively switchfrequency bands based on the quality value generated.
 15. A systemcomprising: a wireless interface having one or more omnidirectionalantennae to communicate utilizing wireless communication protocols; andan agent coupled with the wireless interface to calculate a first SNRvalue for a received signal via the wireless interface using a first SNRequation, to compare the first SNR value against a threshold value, tocalculate a second SNR value using a second SNR equation based on theresult of the comparison and to utilize the second SNR value toselectively modify operational parameters.
 16. The system of claim 15wherein the first SNR equation comprises(log₂ |X|−log₂ |E−|X||)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(1,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being Additive WhiteGaussian Noise (AWGN).
 17. The system of claim 15 wherein calculating asecond SNR value using a second SNR equation based on the result of thecomparison comprises setting the second SNR value equal to the first SNRvalue if the first SNR value is lower than the threshold.
 18. The systemof claim 15 wherein the second SNR equation comprises:(log₂(2|X| ²)−log₂ |E ² −|X| ²|)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being AWGN noises, tocalculate the second SNR value if the first SNR value is greater thanthe threshold.
 19. The system of claim 15 wherein selective modificationof operational parameters comprises one or more of adjusting, setting,and determining operational parameters and further wherein theoperational parameters comprise one or more of data connectionparameters, data connection settings, data transmission parameters, anddata transmission settings.
 20. The system of claim 15, wherein theagent is further configured to generate a quality value based, at leastin part, on a difference between the second SNR value and a frequencydomain calculated SNR value.
 21. The system of claim 20, wherein theagent is further configured to selectively switch frequency bands basedon the quality value generated.
 22. An article comprising acomputer-readable storage medium having instructions stored thereonthat, when executed, cause one or more processors to: calculate a firstSNR value for a received signal using a first SNR equation; compare thefirst SNR value against a threshold value; calculate a second SNR valueusing a second SNR equation based on the result of the comparison; andutilize the second SNR value to selectively modify operationalparameters.
 23. The article of claim 22 wherein the first SNR equationcomprises(log₂ |X|−log₂ |E−|X∥)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being Additive WhiteGaussian Noise (AWGN).
 24. The article of claim 22 wherein calculating asecond SNR value using a second SNR equation based on the result of thecomparison comprises setting the second SNR value equal to the first SNRvalue if the first SNR value is lower than the threshold.
 25. Thearticle of claim 22 wherein the second SNR equation comprises:(log₂(2|X| ²)−log₂ |E ² −|X| ²|)(log₁₀ 2), where${X = {2{\sum\limits_{k = 0}^{127}\; {r_{k}r_{k + 128}^{*}}}}},{E = {{\sum\limits_{k = 0}^{255}\; {r_{k}r_{k}^{*}}} = {\sum\limits_{k = 0}^{255}\; {r_{k}}^{2}}}},$and r_(1,128)={r_(k)=s_(k)+n_(k)}_(k=0) ¹²⁷,r_(2,128)={r_(k)=s_(k−128)+n_(k)}_(k=128) ²⁵⁵, with {s_(k)}_(k=0) ¹²⁷being one half of the signal and {n_(k)}_(k=0) ²⁵⁵ being AWGN noises, tocalculate the second SNR value if the first SNR value is greater thanthe threshold.
 26. The article of claim 22 wherein selectivemodification of operational parameters comprises one or more ofadjusting, setting, and determining operational parameters and furtherwherein the operational parameters comprise one or more of dataconnection parameters, data connection settings, data transmissionparameters, and data transmission settings.
 27. The article of claim 22further comprising generating a quality value based, at least in part,on a difference between the second SNR value and a frequency domaincalculated SNR value.
 28. The method of claim 27 further comprisingselectively switching frequency bands based on the quality valuegenerated.